### Replication readme for  "Opening up Military Innovation: Causal Effects of Reforms to U.S. Defense Research" by Sabrina T. Howell, Jason Rathje, John Van Reenen and Jun Wong###

Updated 2/2/2025

This replication package includes code that produces all figures and tables in the main manuscript. It also includes a simulated dataset to help readers understand the data structure, since the underlying application data and any other identifying matched data cannot be shared for security purposes. It is proprietary to the U.S. Air Force and not publicly available. The main paper and the appendix describes in more detail the sources of data. 

The dataset is at the proposal level. Each observation identifies a proposal `proposal_number` by a firm identified by `firm_id_n` to a particular SBIR topic, identified by `topic_n`. The variable `open` specifies whether a topic is an Open topic. `conv` specifies whether a topic is a conventional topic. Firms may appear multiple times in the dataset. `select` is an indicator for whether a particular proposal was successful. `rank_v2` represent the firm's rank within the topic. `total_score_orig` is the score that a proposal received, and `total_score_norm` is the normalized total score. `tvar_ac_dissim` is the non-specificity measure as described in the paper.

Any variable with the prefix `pre` represent the firm's outcome prior to the specific proposal's submission. Any variable with the prefix `post` represent the firm's outcome _after_ the proposal's submission. For example, `any_post_total_patent1095` represents whether a firm has any patent 3 years after the proposal submission.

The simulated dataset does not fully capture the underlying data structure. In particular, table3.do does not run because it requires within-topic variation of employment and age, which the simulated data does not contain.

